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In this paper we derive robust super- and subhedging dualities for contingent claims that can depend on several underlying assets. In addition to strict super- and subhedging, we also consider relaxed versions which, instead of eliminating…

Mathematical Finance · Quantitative Finance 2017-09-14 Patrick Cheridito , Michael Kupper , Ludovic Tangpi

Our paper contributes to the theory of conditional risk measures and conditional certainty equivalents. We adopt a random modular approach which proved to be effective in the study of modular convex analysis and conditional risk measures.…

Mathematical Finance · Quantitative Finance 2022-11-10 Giulio Principi , Fabio Maccheroni

In financial and actuarial research, distortion and Haezendonck-Goovaerts risk measures are attractive due to their strong properties. They have so far been treated separately. In this paper, following a suggestion by Goovaerts, Linders,…

Risk Management · Quantitative Finance 2025-12-04 Aline Goulard , Karl Grosse-Erdmann

To achieve robustness of risk across different assets, risk parity investing rules, a particular state of risk contributions, have grown in popularity over the previous few decades. To generalize the concept of risk contribution from the…

Mathematical Finance · Quantitative Finance 2022-02-22 Mengjin Zhao , Guangyan Jia

This paper deals with three major types of convergence of probability measures on metric spaces: weak convergence, setwise converges, and convergence in the total variation. First, it describes and compares necessary and sufficient…

Probability · Mathematics 2014-07-04 Eugene A. Feinberg , Pavlo O. Kasyanov , Michael Z. Zgurovsky

Within the context of capital adequacy, we study comonotonicity of risk measures in terms of the primitives of the theory: acceptance sets and eligible, or reference, assets. We show that comonotonicity cannot be characterized by the…

Risk Management · Quantitative Finance 2021-01-21 Pablo Koch-Medina , Cosimo Munari , Gregor Svindland

The aggregation of individual risks in large credit and insurance portfolios is guided by diversification and the law of large numbers, which formalizes the convergence of sample averages to their means. At the same time, regulatory capital…

Risk Management · Quantitative Finance 2026-05-19 Max Nendel

Informally, a risk measure is said to be elicitable if there exists a suitable scoring function such that minimizing its expected value recovers the risk measure. In this paper, we analyze the elicitability properties of the class of return…

Risk Management · Quantitative Finance 2023-03-20 Mücahit Aygün , Fabio Bellini , Roger J. A. Laeven

We consider monotone mean-variance (MMV) portfolio selection problems with a conic convex constraint under diffusion models, and their counterpart problems under mean-variance (MV) preferences. We obtain the precommitted optimal strategies…

Portfolio Management · Quantitative Finance 2022-06-01 Yang Shen , Bin Zou

This paper presents a systematic study of the notion of surplus invariance, which plays a natural and important role in the theory of risk measures and capital requirements. So far, this notion has been investigated in the setting of some…

Mathematical Finance · Quantitative Finance 2018-05-16 Niushan Gao , Cosimo Munari

We propose a definition of diversification as a binary relationship between financial portfolios. According to it, a convex linear combination of several risk positions with some weights is considered to be less risky than the probabilistic…

Risk Management · Quantitative Finance 2022-04-05 Maria Logvaneva , Mikhail Tselishchev

In this paper, we propose the multivariate range Value-at-Risk (MRVaR) and the multivariate range covariance (MRCov) as two risk measures and explore their desirable properties in risk management. In particular, we explain that such…

Statistics Theory · Mathematics 2023-05-17 Baishuai Zuo , Chuancun Yin , Jing Yao

Scalar dynamic risk measures for univariate positions in continuous time are commonly represented as backward stochastic differential equations. In the multivariate setting, dynamic risk measures have been defined and studied as families of…

Risk Management · Quantitative Finance 2021-01-19 Çağın Ararat , Zachary Feinstein

We extend techniques and learnings about the stochastic properties of nonlinear responses from finance to medicine, particularly oncology where it can inform dosing and intervention. We define antifragility. We propose uses of risk analysis…

Quantitative Methods · Quantitative Biology 2023-03-22 Nassim Nicholas Taleb , Jeffrey West

Systemic risk measures were introduced to capture the global risk and the corresponding contagion effects that is generated by an interconnected system of financial institutions. To this purpose, two approaches were suggested. In the first…

Optimization and Control · Mathematics 2024-02-23 Sarah Kaakai , Anis Matoussi , Achraf Tamtalini

Under appropriate integrability conditions the risk measure of the sample measures for a law invariant risk measure converge almost surely to the risk measure of the sampled random variable. The results follow from general convergence…

Probability · Mathematics 2021-09-23 Freddy Delbaen

Higher order risk measures are stochastic optimization problems by design, and for this reason they enjoy valuable properties in optimization under uncertainties. They nicely integrate with stochastic optimization problems, as has been…

Risk Management · Quantitative Finance 2024-02-26 Alois Pichler

Model uncertainty has been one prominent issue both in the theory of risk measures and in practice such as financial risk management and regulation. Motivated by this observation, in this paper, we take a new perspective to describe the…

Theoretical Economics · Economics 2025-04-14 Shuo Gong , Yijun Hu , Linxiao Wei

We consider the problem of finding Pareto-optimal allocations of risk among finitely many agents. The associated individual risk measures are law invariant, but with respect to agent-dependent and potentially heterogeneous reference…

Risk Management · Quantitative Finance 2022-05-05 Felix-Benedikt Liebrich

Most high-dimensional estimation and prediction methods propose to minimize a cost function (empirical risk) that is written as a sum of losses associated to each data point. In this paper we focus on the case of non-convex losses, which is…

Machine Learning · Statistics 2017-01-17 Song Mei , Yu Bai , Andrea Montanari